In various image processing applications, it may be desirable to track an object, such as a feature (e.g., face, facial feature, etc.), between successive frames in a video. In order to track a feature from one frame to the next, each frame may be analyzed to determine the new location of the feature. However, analyzing each frame may be a computationally intensive process which may be a challenge, at least for those devices with limited computational resources, to perform in an efficient and timely manner.
Feature tracking may be computationally intensive for various reasons. For example, some feature tracking techniques analyze each entire frame or at least a relatively large portion of each frame. As such, it would be desirable to provide an improved technique for feature tracking between frames, such as frames of a video that provides accurate results with reduced computational requirements.